Units

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Sample subject outline - Semester 2 2013

Note: Subject outlines often change before the semester begins. Below is a sample outline.

Rationale

Generalised linear models (GLMs) cover: simple linear regression, multiple regression, logistic regression, Poisson regression and repeated measures analysis. GLMs provide a unifying framework for many these techniques and they also illustrate the ideas of statistical modelling. Understanding GLMs therefore gives a researcher a access to a powerful and varied set of statistical modelling techniques.

Aims

This unit aims to provide you with an understanding and practical experience of a range of intermediate and relatively complex design concepts and statistical techniques that are commonly applied to the design or analysis of health data.

Objectives

At the completion of this unit it is expected that students will be able to:

At the completion of this unit it is expected that students will be able to:


1. Select the most appropriate regression model for a study;
   
2. Conduct a variety of commonly used modelling techniques used in population health research;
   
3. Create tabular and graphical output suitable for a report for a range of statistical models;
   
4. Check the assumptions and appropriateness of a statistical model;
   
5. Use the SPSS software package, including syntax creation to apply a variety of regression models to health datasets;
   
6. Interpret and report on analyses for a range of research questions and data sets.

Content

Although the course contains some theory (mostly in the first 2 weeks) there will be a strong emphasis on applying concepts through the analysis and interpretation of real-world data-sets. The first 2 weeks cover some difficult concepts and are not as practical as later weeks. However, these concepts are vital for you to be able to fully understand the practical application that follows. For example, you need to be able to understand maximum likelihood to understand almost any statistical model.

Approaches to Teaching and Learning

The unit is taught via on-campus option only. Students will attend up to 4 contact hours per week for 13 weeks (lectures and tutorials). Lectures introduce key concepts that will be reinforced by self-directed reading/learning. Primary learning will be through computer-based tutorials (using SPSS), which are designed to promote application of analytical techniques and critical evaluation of the analytical approaches and presentation of other researchers. Lecture slide material will be posted to the HLN706 Blackboard site on a weekly basis, so that all students may access these summary notes. Go to: http://blackboard.qut.edu.au. The lectures will also be recorded and an audio file placed on Blackboard, although this is only as a back-up and cannot be guaranteed to work or be of good quality.

The Blackboard site will be used to post lecture materials, workshop activities and datasets, and to post notices of which the whole student group for this unit needs to be aware. For example, responses to questions about assessment clarification asked during lectures will be posted to the site for all students to access. It is therefore important that students access the site at least weekly.

Assessment

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Assessment name: Quiz/Test
Description: Formative and Summative Assessment: Short answers and multiple response questions.
Relates to objectives: 1,6
Weight: 20%
Internal or external: Internal
Group or individual: Individual
Due date: Approx. Week 5

Assessment name: Practical Analysis #1
Description: Formative and Summative Assessment: Analysis of a small health data set using regression following a written statistical plan. Presentation of statistical output in tables and graphs. A discussion of the main results and limitations.
Relates to objectives: 2,3,4,5,6
Weight: 30%
Internal or external: Internal
Group or individual: Individual
Due date: Approx. Week 9

Assessment name: Practical Analysis #2
Description: Summative Assessment: Analysis of a large and complex health data set using varied regression techniques. Presentation of statistical plan. Presentation of statistical output in tables and graphs. A discussion of the main results and limitations.
Relates to objectives: 1-6
Weight: 50%
Internal or external: Internal
Group or individual: Individual
Due date: End of Semester

Academic Honesty

QUT is committed to maintaining high academic standards to protect the value of its qualifications. To assist you in assuring the academic integrity of your assessment you are encouraged to make use of the support materials and services available to help you consider and check your assessment items. Important information about the university's approach to academic integrity of assessment is on your unit Blackboard site.

A breach of academic integrity is regarded as Student Misconduct and can lead to the imposition of penalties.

Resource materials

Required Textbook:

Dobson, A J and Barnett, A G. (2008). An Introduction to Generalized Linear Models. 3rd ed. Boca Raton: CRC Press.



OR the second edition



Dobson, A J. (2002). An Introduction to Generalized Linear Models. 2nd ed. Boca Raton: CRC Press.

Risk assessment statement

Computer-based work will be required in workshops and in the preparation of assessment items. Students should ensure that their workstations are adjusted in accordance with Occupational Health and Safety guidelines and that regular rest breaks are taken.

Disclaimer - Offer of some units is subject to viability, and information in these Unit Outlines is subject to change prior to commencement of semester.

Last modified: 13-Jul-2012